The Illness/Injury Sensitivity Index: an examination of construct validity
Bibliographic record
Abstract
The 11-item Illness/Injury Sensitivity Index [ISI; Taylor, 1993: J Behav Ther Exp Psychiatry 24:289-299] measures fears of injury and illness and has the potential to delineate some mechanisms underlying anxiety-associated chronic health conditions. In a principal components analysis in 2005, Carleton et al. [2005a: J Psychopathol Behav Assess 27:235-241] indicated that a two-factor solution (Fear of Injury and Fear of Illness) best explained the structure of the ISI. The primary purpose of this study was to examine the structural and construct validity of the ISI. Results supported a two-factor solution after removal of two overinclusive items. Although the measure demonstrated good factorial validity, convergent and discriminant validity require further evaluation. In addition, a substantial correlation with fear of pain suggests a shift in our perspective on what constitutes a fundamental fear. Future research implications are discussed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".